AWS re:Invent is all about how managed data services, serverless, and AI work together to enable new business applications. The focus is shifting from building the infrastructure of your choice in a playground that has an endless number of toys (services) to an opinionated, pre-packaged approach that enables customers to focus on business applications.
Businesses are aligning with the digital age, as the world becomes increasingly digital. The ability to attract new customers and ensure retention depends on constant delivery of new interactive services which leverage a variety of data assets and AI. Furthermore, profitability depends on automated and optimized operations, which surprisingly enough, also require data and AI technologies. A great example is the Amazon store, where customers receive product recommendations and robots handle packing and shipping.
This means that we need to run fast – faster than our competitors – and focus on applications as opposed to infrastructure hassles. AWS gets that, which is why it’s climbing up the stack with an integrated approach. Forward thinking companies and startups get it as well and therefore challenge incumbent vendors, but most enterprises are still struggling with legacy approaches.
If you think that buying some virtualization or HCI (hyper-converged) cluster, or even playing with Kubernetes is “cloud native,” think again (see my post). You need to build and support the entire stack; use an endless number of commercial or open-source packages; integrate them; make sure they scale, work together and don’t break; integrate security; think about high-availability and service upgrades; patching of OS and hardware… and the list goes on. Companies are left with no time or resources to deal with actual modern applications, which are the whole point.
Moreover, running machine learning algorithms to “identify anomalies” or writing a weekly report about trends doesn’t necessarily make you digital. You are not digital if your data analysis results and AI algorithms are not used as part of an interactive user portal, or to drive real-time actions which save labor or resources.
Businesses must shift their focus from building an infrastructure and “data lakes,” to delivering digital applications and services faster. New services require continuous data analytics, AI and agile development methodologies (AKA micro-services and serverless).
Cloud is Not a Place
Remember, cloud is not a place. It’s a model for consuming pre-integrated “cloud-native” services such as scale-out databases and analytics tools, identity management, service routing, AI, etc., all accessed through simple APIs. The cloud model lets us focus on business applications instead of on infrastructure.
A cloud experience with continuous data and analytics services, AI, and serverless, can be delivered close to your data sources at the edge, on-premises or in a data center and doesn’t have to be in the public cloud.